AI Architecture Lead
Quick Summary
Job Description Purpose of the role To provide quantitative and analytical expertise to support trading strategies, risk management, and decision-making within the investment banking domain,
To provide quantitative and analytical expertise to support trading strategies, risk management, and decision-making within the investment banking domain, applying quantitative analysis, mathematical modelling, and technology to optimise trading and investment opportunities.
- To manage a business function, providing significant input to function wide strategic initiatives. Contribute to and influence policy and procedures for the function and plan, manage and consult on multiple complex and critical strategic projects, which may be business wide..
- They manage the direction of a large team or sub-function, leading other people managers and embedding a performance culture aligned to the values of the business. Or for an individual contributor, they lead organisation wide projects and act as deep technical expert and thought leader, identifying new ways of working and collaborating cross functionally. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
- Provide expert advice to senior functional management and committees to influence decisions made outside of own function, offering significant input to function wide strategic initiatives.
- Manage, coordinate and enable resourcing, budgeting and policy creation for a significant sub-function.
- Escalates breaches of policies / procedure appropriately.
- Foster and guide compliance, ensure regulations are observed that relevant processes in place to facilitate adherence.
- Focus on the external environment, regulators, or advocacy groups to both monitor and influence on behalf of Barclays, when appropriate.
- Demonstrate extensive knowledge of how the function integrates with the business division / Group to achieve the overall business objectives.
- Maintain broad and comprehensive knowledge of industry theories and practices within own discipline alongside up-to-date relevant sector / functional knowledge, and insight into external market developments / initiatives.
- Use interpretative thinking and advanced analytical skills to solve problems and design solutions in often complex/ sensitive situations.
- Exercise management authority to make significant decisions and certain strategic decisions or recommendations within own area.
- Negotiate with and influence stakeholders at a senior level both internally and externally.
- Act as principal contact point for key clients and counterparts in other functions/ businesses divisions.
- Mandated as a spokesperson for the function and business division.
All Senior Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
- Experience deploying and operating machine learning models within enterprise environments.
- Experience with LLM-powered applications, agent frameworks and retrieval systems.
- Familiarity with prompt engineering, evaluation frameworks and AI safety controls.
- Experience with reinforcement learning, fine-tuning or model customisation techniques.
- Experience with Kubernetes and containerised deployment models.
- Experience managing or designing GPU-enabled environments.
- Experience with distributed training and inference workloads.
- Understanding of vector databases, model serving frameworks and AI infrastructure tooling.
- Experience with cloud platforms such as Azure, AWS or GCP.
- Prior experience in electronic trading, quantitative development or financial markets.
- Experience integrating AI capabilities into business workflows and production systems.
- Familiarity with modern C++ and Python-based quantitative environments.
Location & Eligibility
Listing Details
- Posted
- September 9, 2026
- First seen
- September 27, 2026
- Last seen
- September 27, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 23%
- Scored at
- September 27, 2026
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